From: Daulat Ram <Daulat.Ram@cyient.com>
To: pgsql-performance@postgresql.org <pgsql-performance@postgresql.org>
Subject: Query is very much slow
Date: Thu, 25 May 2017 05:13:26 +0000
Message-ID: <e226d5c404cf4cf69ef39354aaab2de0@cyient.com> (raw)
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Hi team,
We are getting very slow response of this query.
SELECT date_trunc('day', insert_time),workflow.project.project_name,
workflow.tool_performance.project_id,workflow.tool_performance.user_id,workflow.tool_performance.step_id,count(*),
round(sum(execution_time)/1000) as Sum_time_sec,round(((round(sum(execution_time)/1000))/60)/count(*),2) as Efficency_Min,round
(((round(sum(execution_time)/1000)))/count(*),2)
as Efficency_sec FROM workflow.project,workflow.tool_performance,workflow.evidence_to_do WHERE workflow.project
.project_id = workflow.tool_performance.project_id AND insert_time >'2017-05-01' AND insert_time <'2017-05-02' AND
workflow.evidence_to_do.status_id in (15100,15150,15200,15300,15400,15500) Group BY date_trunc('day', insert_time),workflow.project.project_name,
workflow.tool_performance.project_id,workflow.tool_performance.user_id,workflow.tool_performance.step_id ORDER BY
workflow.tool_performance.project_id,workflow.project.project_name,
workflow.tool_performance.step_id;
The following indexes are created on project & evidence_to_do table.
"CREATE INDEX project_id_idx ON workflow.project USING btree (project_id)"
"CREATE INDEX evidence_to_do_status_id_index ON workflow.evidence_to_do USING btree (status_id)"
Explain plan of the Query is:
"GroupAggregate (cost=18675703613.60..20443753075.67 rows=6689718 width=69)"
" -> Sort (cost=18675703613.60..18823015982.33 rows=58924947492 width=69)"
" Sort Key: tool_performance.project_id, project.project_name, tool_performance.step_id, (date_trunc('day'::text, tool_performance.insert_time)), tool_performance.user_id"
" -> Nested Loop (cost=2.42..884042104.67 rows=58924947492 width=69)"
" -> Seq Scan on evidence_to_do (cost=0.00..118722.17 rows=554922 width=0)"
" Filter: (status_id = ANY ('{15100,15150,15200,15300,15400,15500}'::bigint[]))"
" -> Materialize (cost=2.42..49435.58 rows=106186 width=69)"
" -> Hash Join (cost=2.42..48904.65 rows=106186 width=69)"
" Hash Cond: (tool_performance.project_id = project.project_id)"
" -> Seq Scan on tool_performance (cost=0.00..47442.18 rows=106186 width=39)"
" Filter: ((insert_time > '2017-05-01 00:00:00+05:30'::timestamp with time zone) AND (insert_time < '2017-05-02 00:00:00+05:30'::timestamp with time zone))"
" -> Hash (cost=1.63..1.63 rows=63 width=38)"
" -> Seq Scan on project (cost=0.00..1.63 rows=63 width=38)"
We have 64 GB of RAM &
CPU(s): 40
Thread(s) per core: 2
Core(s) per socket: 10
Socket(s): 2
PostgreSQL.conf parameter:
shared_buffers =16GB
work_mem =32MB
Would you please help how we can tune this query at database & code level.
Regards Daulat
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To: pgsql-performance@postgresql.org
Cc: Daulat.Ram@cyient.com
Subject: Re: Query is very much slow
In-Reply-To: <e226d5c404cf4cf69ef39354aaab2de0@cyient.com>
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